Deidentifying Narrative Assessments to Facilitate Data Sharing in Medical Education.

Authors from 3 institutions, including 3 emergency medicine programs, an anesthesia program, and a surgical program, participated in formal testing. In the final round of review, 99.4% of the narrative assessments were fully deidentified (names, nicknames, and pronouns removed). The results were comparable for each institution and specialty. The data review interface was improved with feedback obtained after each round of review and found to be intuitive.Next StepsThis innovation has demonstrated viability evidence of an algorithmic approach to the deidentification of assessment narratives while reinforcing that a small number of errors are likely to persist. Future steps include the refinement of both the algorithm to improve its accuracy and the data review interface to support additional data set formats.